The present disclosure generally relates to, field of signal analysis, and more specifically relates to techniques for improving the signal-to-interference-plus-noise ratio (SINR) for signals in the presence of interference. For any particular signal, the presence of interference from other signals causes degradation in the performance of various signal processing algorithms (e.g. demodulation, specific emitter identification (SEI), etc.). We consider the case where multiple interfering signals are of the same type (e.g. CDMA signals in a cellular network). A conventional technique for improving the SINRs of individual signals within a mixture of signals is to demodulate the one received at the largest power, remodulate the signal to create a reference signal, and subtract off the portion of the mixture due to the reference signal. This is termed successive interference cancellation (SIC), and results in a mixture in which each of the remaining signals has an improved SINR. In the past, SIC has been performed with a priori knowledge of signal parameters (e.g. spreading codes), as well as with the ability to apply previous estimates of the channel responses experienced by each signal. In this application, we present a system that does not require these assumptions.